291. Impact of Incidence of Bovine Respiratory Disease (BRD) Detected Using Automated-Disease-Detection (ADD) Technology on Performance, Feed Intake, Efficiency and Feeding Behavior Patterns in Growing Seedstock Bulls.

Clicks: 14
ID: 330293
2026
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #314 of 847 articles by views in italian journal of animal science

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 847 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
Abstract The objective of this study was to examine the impact of BRD, as detected by a novel automated disease-detection system (ADD; SenseHub® tags), on performance, feed intake and efficiency and feeding and drinking behavior patterns in growing seedstock bulls. Across 4 fall and 4 spring feeding trials, 1,945 spring-born bulls (Angus, Simmental, South Devon, and composite breeds) were housed in pens equipped with SmartFeed® and SmartScale® (C-Lock, Inc.) systems to measure daily BW, DMI and behavior traits—including frequencies and duration of bunk-visit (BV), meal, and drinking events, time to approach feed bunk following feed delivery (TTB), and day-to-day variation of DMI and feeding behaviors for 56 d. SenseHub® tags were deployed to detect BRD cases concurrently prior to and during the fall feeding trials (52% incidence of BRD) and for 60 d in the fall prior to the spring feeding trials (48% incidence of BRD). The ADD system continuously monitored activity and ear canal temperature to assess BRD alerts based on deviations from individual baseline values, with BRD cases receiving antimicrobial treatment based on a standardized protocol. Bulls with 1 or 2 cases of BRD during the fall feeding trials had reduced (P < 0.001) DMI and lower (P < 0.001) RFI as actual DMI was reduced to a greater extent than expected DMI based on ADG and mid-test BW compared to non-BRD bulls. Additionally, bulls with 1 or 2 cases of BRD during the fall trials had greater (P < 0.001) TTB and more daily variation in DMI and frequency and duration of BV events than non-BRD bulls. Bulls with 2 BRD cases had reduced DMI and ADG, and lower RFI compared to bulls with only 1 BRD case during the fall trials. Bulls with BRD prior to the fall trials were minimally affected compared to non-BRD bulls. BRD cases were not detected during the spring trials, although bulls with BRD detected prior to the spring trials had lower (P < 0.001) initial BW and greater ADG and G:F than non-BRD bulls, consistent with compensatory gain responses. However, bulls with BRD prior to the spring trials had similar DMI, RFI and feeding behaviors compared to non-BRD bulls. Detection of BRD prior to or during the fall and spring trials did not affect drinking behavior. These results demonstrate that use of ADD technology for detection of BRD was effective, as bulls with BRD during the fall trials had substantial reductions in DMI, took longer to approach feedbunks following feed delivery and had greater daily variation in DMI and feeding events compared to non-BRD bulls. Further, results indicated that bulls with BRD detected 30 to 60 d prior to the fall or spring trials had minimal effects on DMI or RFI.
Reference Key
openalex_W7214731210 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors
Journal italian journal of animal science
Year 2026
DOI
10.1093/jas/skag272.236
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.